Artificial Intelligence Clustering Approach for Force Mapping Analysis of Polyacrylic Acid (PAA)/Polyethylene Oxide...

Biocompatibility of a biosensor can be achieved by grafting polymer brushes onto a solid surface. These brushes must be able to attract specific analytes or repel unwanted entities. This is obtained with weak polyelectrolyte polymer brushes that shrink or swell depending on external stimuli. In this study, the conformation of polyacrylic acid (PAA) and polyethylene oxide (PEO) polymer brushes was characterized as a function of pH and ionic strength using Atomic Force Microscopy (AFM) in spectroscopic mode. Instead of colloidal tips classically used to measure the mechanical behavior of the brush, force curves were performed with conventional tips for better sensitivity to the interaction between ions and polymer, which is responsible for their conformation. Since force mapping experiments generate thousands of curves, a statistical representation was employed to define the general trend of the curves and facilitate their interpretation. As expected, the neutral PEO is not affected by changes in solution pH and salinity. In contrast, PAA exhibits behaviors depending on the ions present in the solution and increasing salinity; the brush shrinks at low pH with H₃O⁺ ions and swells with the addition of Na⁺ and K⁺ ions. The originality of the study also lies in the implementation of an Artificial Intelligence (AI) clustering model applied to force curves to specifically study a 50% PAA/50% PEO mixed polymer brush. This AI model makes it possible to distinguish areas of the surface where only one type of polymer has been grafted and to identify its nature according to its force curve.